Run
10436380

Run 10436380

Task 9985 (Supervised Classification) first-order-theorem-proving Uploaded 23-01-2020 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.cl asses.SVC)(1)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"median"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.preprocessing.data.StandardScaler(29)_copytrue
sklearn.preprocessing.data.StandardScaler(29)_with_meantrue
sklearn.preprocessing.data.StandardScaler(29)_with_stdtrue
sklearn.svm.classes.SVC(31)_C28.677599558661473
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.8912075035785021
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree5
sklearn.svm.classes.SVC(31)_gamma0.008552645432141457
sklearn.svm.classes.SVC(31)_kernel"rbf"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilityfalse
sklearn.svm.classes.SVC(31)_random_state1
sklearn.svm.classes.SVC(31)_shrinkingtrue
sklearn.svm.classes.SVC(31)_tol0.001
sklearn.svm.classes.SVC(31)_verbosefalse
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_verbosefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

18 Evaluation measures

0.6938 ± 0.0089
Per class
Cross-validation details (10-fold Crossvalidation)
0.5351 ± 0.0093
Per class
Cross-validation details (10-fold Crossvalidation)
0.3817 ± 0.0141
Cross-validation details (10-fold Crossvalidation)
0.4044 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
0.1477 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
0.2508 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.557 ± 0.0092
Cross-validation details (10-fold Crossvalidation)
6118
Per class
Cross-validation details (10-fold Crossvalidation)
0.5362 ± 0.0118
Per class
Cross-validation details (10-fold Crossvalidation)
0.557 ± 0.0092
Cross-validation details (10-fold Crossvalidation)
2.3 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
0.5888 ± 0.0122
Cross-validation details (10-fold Crossvalidation)
0.3541 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.3843 ± 0.004
Cross-validation details (10-fold Crossvalidation)
1.0852 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
0.4186 ± 0.0107
Cross-validation details (10-fold Crossvalidation)